A Particle Swarm Optimization Solution to NO2 and SO2 Emissions for Environmentally Constrained Economic Dispatch Problem

Multi-objective economic emission load dispatch solution using gravitational search algorithm and considering wind power penetration

“…Assuming the equality of the gravitational and inertia masses, the values of masses are calculated using the map of fitness. The gravitational and inertial masses are updated by the following equations: One way to perform a good compromise between exploration and exploitation is to reduce the number of agents with lapse of time in (17). Hence, in this algorithm only a set of agents with bigger mass apply their force to the other.…”

“…At the end there will be just one agent applying force to the others. Therefore, (17) can be modified as:…”

“…Sudhakaran et al [15] applied the refined genetic algorithm (RGA) for the successful operation of the power system subject to economical and environmental constraints. To solve EELD problems, PSO has also been adopted in different papers but in separate styles [16][17][18]. Dhillon and Kothari [19] and Osman et al [20] proposed a novel binary successive approximation-based evolutionary search strategy and multi-objective genetic algorithm respectively to solve the economic-emission load dispatch problem.…”

Backtracking search optimization based economic environmental power dispatch problems

“…In [21], Wei et al discussed minimization of carbon oxide as an emission dispatch for better solution. AlRashidi et al and Thakur et al both tried to provide better solution by applying population based algorithm called particle swarm optimization (PSO) technique [22,23] in EELD problem. Perez-Guerrero RE et al [24] applied another new population based technique differential evolution method to evaluate economic and emission load dispatch by considering either emissions as constraints or cost of generation as a second objective function of a multi-objective optimization problem.…”

Multi Objective Dispatch Problem with Valve Point Effect Loading of Fuel Cost and Emission Criterion

“….The combined fuel cost function and emission function without valve point effect is formulated by Weighted Sum Method (WSM) using PSO algorithm in [17], [18] and Evolutionary programming in [19].The combined fuel cost function and emission function without valve point effect is formulated by various price penalty factors approaches using recursive algorithm in [20]. MaxMax price penalty factor method using quadratic programming in [21], security constrained unit commitment problem algorithm in [22], sequential approach with matrix frame work in [23], PSO in [24], Improved back propagation neural network in [25], and Lagrange's method in [26]. The combined fuel cost function without valve point effect and emission function with valve point effect is formulated using PSO algorithm in [15].…”